曹瑛倬,鲍志东,鲁锴,陈欣怡.京津冀地区雁翎潜山带雾迷山组储层测井识别方法及应用[J].地质找矿论丛,2020,35(2):237-245
京津冀地区雁翎潜山带雾迷山组储层测井识别方法及应用
Logging identification method of the Wumishan Formation carbonate reservoir in Yanling Buried Hills and the application in Beijing-Tianjin-Hebei area
投稿时间:2019-09-23  
DOI:10.6053/j.issn.1001-1412.2020.02.015
中文关键词:  储层识别  碳酸盐岩测井  决策树  雁翎潜山带  京津冀地区
英文关键词:reservoir identification  carbonate logging  decision tree  Yanling Buried Mountain zone  Beijing-Tianjin-Hebei area
基金项目:国家重点研发计划项目(编号:2018YFC0604304、2017YFC0603104)资助。
作者单位E-mail
曹瑛倬 中国石油大学(北京)地球科学学院, 北京 102249  
鲍志东 中国石油大学(北京)地球科学学院, 北京 102249 baozhd@cup.edu.cn 
鲁锴 中国石油大学(北京)地球科学学院, 北京 102249  
陈欣怡 中国石油大学(北京)地球科学学院, 北京 102249  
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中文摘要:
      京津冀地区中低温地热资源丰富,地温梯度普遍大于2.5℃,碳酸盐岩储层埋深在3500 m以浅,地热资源量大,具有良好的开发前景。京津冀地区雁翎潜山带雾迷山组储层属于多期构造和岩溶作用形成的碳酸盐岩缝洞型储层,储集空间复杂,测井识别较为困难。本文作者基于野外观察,结合岩芯、薄片、常规测井、物性数据分析等资料,对研究区雾迷山组碳酸盐岩储层特征进行了研究,将储层进一步划分为裂缝型、孔洞型、复合型和洞穴型4种类型,建立不同类型储层的测井识别标准,并运用决策树方法对研究区雾迷山组碳酸盐岩储层进行系统识别,提高储层预测效率,在前期数据的基础上,建立研究区孔隙度、渗透率模型,拟合效果较为理想。结果表明:研究区储层主要以裂缝型储层和复合型储层为主,孔洞型及洞穴型储层发育较少;基于决策树的储层类别方法识别正确率可达85%以上,数学模型得出的计算孔隙度相对误差为25%,计算渗透率误差在一个数量级以内,符合数据精度要求,结果较为可靠。
英文摘要:
      Medium-low geothermal resources is abundant in Beijing-Tianjin-Hebei area with temperature gra diant generally more thatn 2.5°C and the buried depth of the carbonate reservoir is within 3500 m and huge geothermal resource occurs here with good development prospects. The Wumishan Formation reservoir is a fractured karst cave systems formed by multi-period geological tectonic and karstification. Such reservoir’s accumulation space is complicated and logging identification is difficult. Based on the field observation, the core observation, thin section identification, well logs and physical property data characteristics of the reservoir are studied and the reservoirs are furhterly divided into four types, including fracture reservoir, pore and cave reservoir, complex reservoir and cave reservoir. According to the characteristics of different types of reservoirs,the feature of conventional logging responses of different reservoirs were analyzed and established a standard of the Wumishan Formation reservoir identification in the study area, then using the decision trees to systematically identify and prodict the carbonate reservoirs of the Wumishan Formation in the study area efficiently. Based on the previous data, establish the porosity and permeability models of the study area,have a good fitting effect. The results show that the reservoirs in the study area are mainly fractured reservoirs and fractured-vugular reservoirs, and the vugular reservoirs and cave reservoirs are less developed. The correct rate of reservoir classification based on decision trees can reach more than 85%, The calculated relative porosity error is 25%, and the calculated permeability error is within an order of magnitude, which meets the data accuracy requirements. The results are reliable and can provide theoretical and technical support for the comprehensive evaluation of geothermal reservoirs and this standard and models can provide theoretical and technical support for prodictive evaluation of geothermal reservoirs and favorable zones in the study area.
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